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Response of autaptic Hodgkin–Huxley neuron with noise to subthreshold sinusoidal signals

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  • Wang, Hengtong
  • Chen, Yong

Abstract

In this work, we investigated the response of a stochastic Hodgkin–Huxley (HH) neuron with an autapse to subthreshold sinusoidal signals. It is found that the autapse not only adjusts the stochastic responses, but also improves the detection of subthreshold signals. In the case of weak noise, the autapse facilitates the response of neuron to the subthreshold sinusoidal signals with a small parameter region in tdelay-ω space. The increased noise intensity enlarges this parameter region and increases the corresponding response frequency in such range. As the autaptic intensity increases, however, this parameter region shrunks. We also observed that there is an optimal range of the delay time of autapse, within which the stochastic HH neuron fires action potentials with high frequency. The corresponding response spike train for the optimal delay time is nearly a regular sequence with the interspike intervals approximated to the delay time. The current results reveal a novel resonance phenomenon facilitated by autapse, named autaptic delay-induced coherence resonance.

Suggested Citation

  • Wang, Hengtong & Chen, Yong, 2016. "Response of autaptic Hodgkin–Huxley neuron with noise to subthreshold sinusoidal signals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 321-329.
  • Handle: RePEc:eee:phsmap:v:462:y:2016:i:c:p:321-329
    DOI: 10.1016/j.physa.2016.06.019
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    References listed on IDEAS

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    1. Yilmaz, Ergin & Uzuntarla, Muhammet & Ozer, Mahmut & Perc, Matjaž, 2013. "Stochastic resonance in hybrid scale-free neuronal networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(22), pages 5735-5741.
    2. Yilmaz, Ergin & Baysal, Veli & Ozer, Mahmut & Perc, Matjaž, 2016. "Autaptic pacemaker mediated propagation of weak rhythmic activity across small-world neuronal networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 538-546.
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    Cited by:

    1. Uzun, Rukiye & Yilmaz, Ergin & Ozer, Mahmut, 2017. "Effects of autapse and ion channel block on the collective firing activity of Newman–Watts small-world neuronal networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 386-396.
    2. Ni Zhang & Dongxi Li & Yanya Xing, 2021. "Autapse-induced multiple inverse stochastic resonance in a neural system," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 94(1), pages 1-11, January.
    3. Xiao, Fangli & Fu, Ziying & Jia, Ya & Yang, Lijian, 2023. "Resonance effects in neuronal-astrocyte model with ion channel blockage," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    4. Baysal, Veli & Calim, Ali, 2023. "Stochastic resonance in a single autapse–coupled neuron," Chaos, Solitons & Fractals, Elsevier, vol. 175(P2).
    5. Yu, Haitao & Galán, Roberto F. & Wang, Jiang & Cao, Yibin & Liu, Jing, 2017. "Stochastic resonance, coherence resonance, and spike timing reliability of Hodgkin–Huxley neurons with ion-channel noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 263-275.
    6. Uzun, Rukiye, 2017. "Influences of autapse and channel blockage on multiple coherence resonance in a single neuron," Applied Mathematics and Computation, Elsevier, vol. 315(C), pages 203-210.

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